Characterization of tetracycline- and ampicillin-resistant <i>Escherichia coli</i> isolated from the feces of feedlot cattle over the feeding period
Bibliographic record
Abstract
The objective of this study was to investigate tetracycline and ampicillin resistance in Escherichia coli isolated from the feces of 50 crossbred steers housed in 5 feedlot pens. The steers were not administered antibiotics over a 246-day feeding period. A total of 216 isolates were selected for further characterization. The E. coli isolates were selected on MacConkey agar or on MacConkey agar amended with ampicillin (50 microg/mL) or tetracycline (4 microg/mL). Pulsed-field gel electrophoresis (PFGE) typing (XbaI digestion), screening against 11 antibiotics, and multiplex PCR for 14 tet and 3 beta-lactamase genes were conducted. Prevalence of antimicrobial resistance in E. coli at each sampling day was related both temporally and by pen. Multiplex PCR revealed that tet(B) was most prevalent among tetracycline-resistant isolates, whereas beta-lactamase tem1-like was detected mainly in ampicillin-resistant isolates. Our results suggest that antimicrobial resistance in E. coli populations persists over the duration of the feeding period, even in the absence of in-feed antibiotics. Many of the isolates with the same antibiograms had indistinguishable PFGE patterns. Characterization of the factors that influence the nature of this nonselective resistance could provide important information for consideration in the regulation of in-feed antimicrobials for feedlot cattle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".